Posts filed under General (3005)

• From the BBC “Vitamin D deficiency linked to hospital admissions”. This is from a large British study correlating vitamin D levels in the blood with hospital admissions for respiratory infections. You might say “Someone ought to do a clinical trial to see if giving people vitamin D reduces infections or if  it’s just correlation”. Someone has, here in NZ. Also, if you combine all the trials on this question you get an estimate of somewhere between a 10% reduction and a 4% increase. It’s still possible that it works in people with especially low vitamin D or something, but across a range of diseases randomised clinical trials of vitamin D have been robustly disappointing in comparison to correlational studies.
• From Derek Lowe, a post on extremely bad clinical trial conduct. This isn’t fraud by Big Pharma — if it counts as fraud, Big Pharma is a victim (along with some, but possibly not all, of the trial participants)
• “A very detailed map of Trump’s job approval” from Strength In Numbers (click to embiggen). “The basic idea is that we fit a model predicting approval based on demographics and geography, then use Census data to weight those predictions by the actual population composition of each area. Election results are used to calibrate estimates to sensible baselines, so we have a real-world check against our survey data. It lets us produce reliable estimates even for places where we only have a handful of direct survey respondents.”
  
• From the Guardian, Australian supermarket online prices per each can be very different from the in-store per-kg prices. Most dramatically, green capsicums were allegedly 50% more expensive per each.
• Bogus polls show increases in church attendance by young adults: Pew Research

Right now, it is very cold in the central and eastern United States.  Minneapolis has been in the news (for this as well as the bad sort of ice), but it’s not just there. The Mayor of New York has warned locals about a major snowstorm (and suggested it would be a good time to stay home and borrow the e-book or audiobook of  Heated Rivalry from the city libraries). There’s freezing weather in parts of Texas that are really not built to handle it.

Various people, as usual, have said the cold weather refutes global warming.

As you all know, the issue with global warming  is that it’s global (there’s a hint in the name) rather than local.  I always recommend looking at global temperature patterns.  Here’s the global temperature anomaly, from Climate Reanalyzer, at the University of Maine

The map is based on today’s weather forecast around the world, averaged over 24 hours and compared to the average for the same day of the year from 1979 to 2000.  As you can see, it’s unusually cold in the USA. It’s also unusually cold in a band across Asia. On the other hand, it’s unusually warm in Greenland and the far north of North America and in Siberia.

This image shows a view around the north pole

You can see here the problem is that the cold that belongs up in the Arctic has slipped down over Asia and North America.  There isn’t extra cold in the world, it’s just in unusual places.  This sort of unusual movement of north polar air is perfectly consistent with global warming models.

Team Ratings for the Conference Finals

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 282 matches played, 170 of which were correctly predicted, a success rate of 60.3%.
Here are the predictions for last week’s games.

Predictions for the Conference Finals

Here are the predictions for the Conference Finals. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for the Divisional Finals

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 278 matches played, 167 of which were correctly predicted, a success rate of 60.1%.
Here are the predictions for last week’s games.

Predictions for the Divisional Finals

Here are the predictions for the Divisional Finals. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

The top baby names from 2025 are out, together with historic data to look at trends. Sadly, the historic data for boys’ names and for girls’ names come as three-page PDF tables with very small print, not as some conveniently computer-readable or human-readable format.  We can still see some interesting trends

The top names last year were Noah for boys (244 times) and Isla for girls (179 times). There has always been more variability in girls’ names: there are always more boys with the most popular name than girls with the most popular name.

The total number of births in NZ has been broadly stable since the 1950s but the number of babies with the most popular name has steadily been decreasing, implying increasing name diversity. In 1954 there were 1389 Johns; in 1979 there were 707 Michaels; in 2004 there were 504 Joshuas. For girls, the numbers were 779 Christines in 1954, 578 Sarahs in 1979, and 352 Emmas in 2004.

There aren’t any names that appear in the top 100 for both boys and girls. There are few names that, over history, have been in both lists but I haven’t found any that were in both lists in the same year — the closest was Kim. a top-100 name for boys in 1961 and 1962 and for girls in quite a few years starting from 1968.

This was on a real-estate agent’s advertising leaflet at a local café

If you aren’t from around here, those are neighbourhoods in south central Auckland.

Statisticians often complain about pie charts because it’s hard to make numerical comparisons between the categories, especially compared to a bar chart

The poor visual comparison might actually be a virtue in this case if the point is just that these neighbourhoods are similar.  In any case, there’s a deeper problem: pie charts are fundamentally about the relationship between portions and a total — slices and the whole pie.  In this example there is no meaningful total that the separate medians are components of.  There isn’t a pie for these to be slices of.

From Nicola Rennie on Bluesky, a bad graph found on LinkedIn:

and a correct version of the same graph

The bad version is probably from generative AI — as Nicola says, it is bad in ways that would take substantial effort to achieve in commonly-used software, ranging from the weird bar alignment to the incorrect lengths to the incoherent choice of colours to the Slovenioid flag to the spelling of Belgıun.  It’s also a bit vague about the data source, but that’s easy to achieve by hand.

The corrected version is a lot better, but brings out that this is actually hard to interpret. What’s a “foreign” language?  If you’re Welsh or Irish, can English count? Can Spanish count for the Basques? Less politically, if you’re Czech and you speak Slovak, is that a foreign language? Is it still a foreign language if you learned it before 1992?  If you grew up in Ghent, speaking Flemish and French, and learned English at school then you know one foreign language, but if you move to London do you suddenly know two foreign languages?

You might say “language that is not an official language of where you live”,  which is less ambiguous but does require identifying all the official languages of where you live. These are typically well-known within any the country or region (though there are people who profess to be confused about whether English is an official language of New Zealand), but they can be hard to determine by database search.

Kieran Healy, of Duke, gave an excellent talk last year about “Trustworthy Data Visualisation“: having graphs you can trust is not just about reproducibility in a simple sense, but about the systems that allow you to trust what you see: The important thing is not to lose sight of the collective, cooperative character of the whole enterprise.

Cross-national comparisons require that someone in each country has collected data, that the data answer the question you are interested in, that the biases and edge cases are either unimportant or the same across the countries, that the data have been accumulated, and that someone has drawn a graph.  In the past, all these steps were done by accountable people or organisations who were (or perhaps weren’t) honestly trying to provide good information. All these steps became more accessible over the past few decades, but we may be about to lose it all again.

You might well have good and sufficient reasons to trust your vibe graphics for your purposes.  It’s hard to see how other people can have good and sufficient reasons to trust them, though.

Team Ratings for the Wild Card Games

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 272 matches played, 163 of which were correctly predicted, a success rate of 59.9%.
Here are the predictions for last week’s games.

Predictions for the Wild Card Games

Here are the predictions for the Wild Card Games. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Week 10

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 68 matches played, 45 of which were correctly predicted, a success rate of 66.2%.
Here are the predictions for last week’s games.

Predictions for Week 10

Here are the predictions for Week 10. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 15

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 98 matches played, 80 of which were correctly predicted, a success rate of 81.6%.
Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 15. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.